Background And Aims: Insufficient bowel preparation accounts for up to 42% of missed adenomas in colonoscopy. However, major analysis programs found no correlation between adenoma detection rate and the human-rated Boston Bowel Preparation Scale (BBPS), indicating limitations of the scale. We therefore aimed to develop an open-source automatic bowel preparation scale (OSABPS) based on artificial intelligence that is correlated to the polyp detection rate (PDR).
View Article and Find Full Text PDFObjectives: To evaluate and improve "Making Alternative Treatment Choices Intuitive and Trustworthy" (MATCH-IT)-a digital, interactive decision support tool displaying structured evidence summaries for multiple comparisons-to help physicians interpret and apply evidence from network meta-analysis (NMA) for their clinical decision-making.
Study Design And Setting: We conducted a qualitative user testing study, applying principles from user-centered design in an iterative development process. We recruited a convenience sample of practicing physicians in Norway, Belgium, and Canada, and asked them to interpret structured evidence summaries for multiple comparisons-linked to clinical guideline recommendations-displayed in MATCH-IT.
Introduction: Most epidemiological studies in the field of military medicine have been based on data from medical records and registries. The aims of this study were to test a self-reporting injury surveillance system commonly used in sports medicine in a military setting, and to describe the injury pattern among Norwegian army conscripts during a period of military training.
Method: A total of 296 conscripts in His Majesty the King's Guard were asked to report all injuries each week for 12 weeks, using a modification of the Oslo Sports Trauma Research Center Questionnaire on Health Problems (OSTRC-H2).